NSF grant for big data and machine learning research infrastructure

October 23, 2017

CI-New: Cognitive Hardware and Software Ecosystem Community Intrastructure (CHASE-CI)

MESA Lab is one of the 10 campus participants to this $1M NSF CI grant. We will have much more computing power for big data and deep learning related research. FIONA (Fast I/O Network Appliance) will be ready soon.

The Cubix Expansion chassis houses 8 GTX 1080 Founder’s cards. Here’s more information on that: https://www.cubix.com/wp-content/uploads/2016/08/Xpander-Fiber-8-5URP.pdf

Our previous GPU faccility at MESA Lab is shown here: http://mechatronics.ucmerced.edu/news/2017/congratulations-guoxiang-zhang-and-tiebiao-zhao-winning-nvidiab-gpu-grant-titian-x-pascal  (2 sets)

=== Project Summary ===

This project, called the Cognitive Hardware And Software Ecosystem Community Infrastructure (CHASE-CI), will build a cloud of hundreds of affordable Graphics Processing Units (GPUs), networked together with a variety of neural network machines to facilitate development of next generation cognitive computing. This cloud will be accessible by 30 researchers assembled from 10 universities via the NSF-funded Pacific Research Platform. These researchers will investigate a range of problems from image and video recognition, computer vision, contextual robotics to cognitive neurosciences using the cloud to be purpose-built in this project.

Training of neural network with large data-sets is best performed on GPUs. Lack of availability of affordable GPUs and lack of easy access to the new generation of Non-von Neumann (NvN) machines with embedded neural networks impede research in cognitive computing. The purpose-built cloud will be available over the network to address this bottleneck. PIs will study various Deep Neural Network, Recurrent Neural Network, and Reinforcement Learning Algorithms on this platform.

Last updated 10/23/2017 by Prof. YangQuan Chen.